library(scales)
library(gapminder)
library(tidyverse)
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## ✓ ggplot2 3.3.3     ✓ purrr   0.3.4
## ✓ tibble  3.0.6     ✓ dplyr   1.0.4
## ✓ tidyr   1.1.2     ✓ stringr 1.4.0
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library(gganimate)
data("gapminder")
head(gapminder)
## # A tibble: 6 x 6
##   country     continent  year lifeExp      pop gdpPercap
##   <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
## 1 Afghanistan Asia       1952    28.8  8425333      779.
## 2 Afghanistan Asia       1957    30.3  9240934      821.
## 3 Afghanistan Asia       1962    32.0 10267083      853.
## 4 Afghanistan Asia       1967    34.0 11537966      836.
## 5 Afghanistan Asia       1972    36.1 13079460      740.
## 6 Afghanistan Asia       1977    38.4 14880372      786.
g <- gapminder %>% 
  ggplot(aes(x = gdpPercap, y = lifeExp, color = continent, size = pop ))+
  geom_point(alpha = 0.7, stroke = 0)+
  scale_x_log10(label=comma)+
  transition_time(year)+
  labs(subtitle = "year: {frame_time}")
  
  
animate(g, height = 500, width = 800, fps = 60, duration = 10, end_pause = 60, res = 100)

#anim_save("gapminder graph.gif")
library(plotly)
## 
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## 
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## 
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quakes = read.csv('https://raw.githubusercontent.com/plotly/datasets/master/earthquakes-23k.csv')

fig <- quakes 
fig <- fig %>%
  plot_ly(
    type = 'densitymapbox',
    lat = ~Latitude,
    lon = ~Longitude,
    coloraxis = 'coloraxis',
    radius = 10) 
fig <- fig %>%
  layout(
    mapbox = list(
      style="stamen-terrain",
      center= list(lon=180)), coloraxis = list(colorscale = "Viridis"))

fig
library(plotly)
library(gapminder)

df <- gapminder 
fig <- df %>%
  plot_ly(
    x = ~gdpPercap, 
    y = ~lifeExp, 
    size = ~pop, 
    color = ~continent, 
    frame = ~year, 
    text = ~country, 
    hoverinfo = "text",
    type = 'scatter',
    mode = 'markers'
  )
fig <- fig %>% layout(
    xaxis = list(
      type = "log"
    )
  )
fig
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